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| Section | Weight | Objectives |
|---|---|---|
| OCI Data Science Service | 30% | - Model catalog
|
| Machine Learning Fundamentals | 20% | - Unsupervised learning
|
| Model Development and Deployment | 30% | - Model training
|
| MLOps and OCI Integration | 20% | - Automation and pipelines
|
1. Which of the following programming languages are most widely used by data scientists?
A) Python, R, and SQL
B) C and C++
C) Java and JavaScript
2. You are working as a data scientist for a healthcare company. They decide to analyze the data to find patterns in a large volume of electronic medical records. You are asked to build a PySpark solution to analyze these records in a JupyterLab notebook. What is the order of recommended stepsto develop a PySpark application in Oracle Cloud Infrastructure (OCI) Data Science?
A) Launch a notebook session, configure core-site.xml, install a PySpark conda environment, develop your PySpark application, create a Data Flow application with the Accelerated Data Science (ADS) SDK
B) Launch a notebook session, install a PySpark conda environment, configure core-site.xml, develop your PySpark application, create a Data Flow application with the Accelerated Data Science (ADS) SDK
C) Configure core-site.xml, install a PySpark conda environment, create a Data Flow application with the Accelerated Data Science (ADS) SDK, develop your PySpark application, launch a notebook session
D) Install a Spark conda environment, configure core-site.xml, launch a notebook session, create a Data Flow application with the Accelerated Data Science (ADS) SDK, develop your PySpark application
3. You have an embarrassingly parallel or distributed batch job on a large amount of data that you consider running using Data Science Jobs. What would be the best approach to run the workload?
A) Create a new job for every job run that you have to run in parallel, because the Data Science Jobs service can have only one job run per job
B) Reconfigure the job run because Data Science Jobs does not support embarrassingly parallel workloads
C) Create the job in Data Science Jobs and then start the number of simultaneous job runs required for your workload
D) Create the job in Data Science Jobs and start a job run. When it is done, start a new job run until you achieve the number of runs required
4. Arrange the following in the correct Git Repository workflow order:
Install, configure, and authenticate Git.
Configure SSH keys for the Git repository.
Create a local and remote Git repository.
Commit files to the local Git repository.
Push the commit to the remote Git repository.
A) 4, 2, 3, 1, 5
B) 3, 5, 1, 2, 4
C) 1, 2, 3, 4, 5
D) 2, 3, 1, 4, 5
5. What is the name of the machine learning library used in Apache Spark?
A) GraphX
B) MLib
C) Structured Streaming
D) HadoopML
Solutions:
| Question # 1 Answer: A | Question # 2 Answer: B | Question # 3 Answer: C | Question # 4 Answer: C | Question # 5 Answer: B |
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